Lending Club Profiling Report

Dataset statistics

Number of variables	33
Number of observations	134804
Missing cells	235490
Missing cells (%)	5.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	33.9 MiB
Average record size in memory	264.0 B

Variable types

Numeric	15
Unsupported	1
Categorical	17

Warnings

`application_type` has constant value "Individual"	Constant
`desc` has a high cardinality: 48034 distinct values	High cardinality
`earliest_cr_line` has a high cardinality: 607 distinct values	High cardinality
`emp_title` has a high cardinality: 83424 distinct values	High cardinality
`title` has a high cardinality: 32326 distinct values	High cardinality
`zip_code` has a high cardinality: 834 distinct values	High cardinality
`fico_range_high` is highly correlated with `fico_range_low`	High correlation
`fico_range_low` is highly correlated with `fico_range_high`	High correlation
`installment` is highly correlated with `loan_amnt`	High correlation
`loan_amnt` is highly correlated with `installment`	High correlation
`grade` is highly correlated with `application_type` and 1 other fields	High correlation
`addr_state` is highly correlated with `application_type`	High correlation
`term` is highly correlated with `application_type`	High correlation
`verification_status` is highly correlated with `application_type`	High correlation
`application_type` is highly correlated with `grade` and 10 other fields	High correlation
`purpose` is highly correlated with `application_type`	High correlation
`emp_length` is highly correlated with `application_type`	High correlation
`home_ownership` is highly correlated with `application_type`	High correlation
`initial_list_status` is highly correlated with `application_type`	High correlation
`loan_status` is highly correlated with `application_type`	High correlation
`sub_grade` is highly correlated with `grade` and 1 other fields	High correlation
`issue_d` is highly correlated with `application_type`	High correlation
`member_id` has 134804 (100.0%) missing values	Missing
`desc` has 86076 (63.9%) missing values	Missing
`emp_length` has 5962 (4.4%) missing values	Missing
`emp_title` has 8565 (6.4%) missing values	Missing
`pub_rec` is highly skewed (γ1 = 24.06241939)	Skewed
`revol_bal` is highly skewed (γ1 = 27.9368739)	Skewed
`desc` is uniformly distributed	Uniform
`id` has unique values	Unique
`member_id` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`mort_acc` has 51653 (38.3%) zeros	Zeros
`pub_rec` has 118805 (88.1%) zeros	Zeros
`pub_rec_bankruptcies` has 120491 (89.4%) zeros	Zeros

Reproduction

Analysis started	2021-04-19 13:53:16.288120
Analysis finished	2021-04-19 13:54:29.863297
Duration	1 minute and 13.58 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

id
Real number (ℝ_≥0)

UNIQUE

Distinct	134804
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	6289701.213
Minimum	356706
Maximum	10234817
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	356706
5-th percentile	3153423.35
Q1	4525783.75
median	6328041
Q3	7725887.75
95-th percentile	9736300.05
Maximum	10234817
Range	9878111
Interquartile range (IQR)	3200104

Descriptive statistics

Standard deviation	2073468.969
Coefficient of variation (CV)	0.3296609646
Kurtosis	-0.9958781613
Mean	6289701.213
Median Absolute Deviation (MAD)	1716915.5
Skewness	-0.01644913247
Sum	8.478768823 × 10¹¹
Variance	4.299273566 × 10¹²
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4196351	1	< 0.1%
5624976	1	< 0.1%
9827476	1	< 0.1%
5784894	1	< 0.1%
6415510	1	< 0.1%
5606555	1	< 0.1%
5616796	1	< 0.1%
4309553	1	< 0.1%
4566175	1	< 0.1%
9194659	1	< 0.1%
Other values (134794)	134794	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
356706	1	< 0.1%
380041	1	< 0.1%
442319	1	< 0.1%
476326	1	< 0.1%
546966	1	< 0.1%

Value	Count	Frequency (%)
10234817	1	< 0.1%
10234814	1	< 0.1%
10234813	1	< 0.1%
10234796	1	< 0.1%
10234762	1	< 0.1%

member_id
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	134804
Missing (%)	100.0%
Memory size	1.0 MiB

loan_status
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

Fully Paid	113780
Charged Off	21024

Length

Max length	11
Median length	10
Mean length	10.15595976
Min length	10

Characters and Unicode

Total characters	1369064
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Fully Paid
2nd row	Fully Paid
3rd row	Fully Paid
4th row	Fully Paid
5th row	Fully Paid

Value	Count	Frequency (%)
Fully Paid	113780	84.4%
Charged Off	21024	15.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
paid	113780	42.2%
fully	113780	42.2%
off	21024	7.8%
charged	21024	7.8%

Most occurring characters

Value	Count	Frequency (%)
l	227560	16.6%
	134804	9.8%
a	134804	9.8%
d	134804	9.8%
F	113780	8.3%
u	113780	8.3%
y	113780	8.3%
P	113780	8.3%
i	113780	8.3%
f	42048	3.1%
Other values (6)	126144	9.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	964652	70.5%
Uppercase Letter	269608	19.7%
Space Separator	134804	9.8%

Most frequent character per category

Value	Count	Frequency (%)
l	227560	23.6%
a	134804	14.0%
d	134804	14.0%
u	113780	11.8%
y	113780	11.8%
i	113780	11.8%
f	42048	4.4%
h	21024	2.2%
r	21024	2.2%
g	21024	2.2%

Value	Count	Frequency (%)
F	113780	42.2%
P	113780	42.2%
C	21024	7.8%
O	21024	7.8%

Value	Count	Frequency (%)
	134804	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1234260	90.2%
Common	134804	9.8%

Most frequent character per script

Value	Count	Frequency (%)
l	227560	18.4%
a	134804	10.9%
d	134804	10.9%
F	113780	9.2%
u	113780	9.2%
y	113780	9.2%
P	113780	9.2%
i	113780	9.2%
f	42048	3.4%
C	21024	1.7%
Other values (5)	105120	8.5%

Value	Count	Frequency (%)
	134804	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1369064	100.0%

Most frequent character per block

Value	Count	Frequency (%)
l	227560	16.6%
	134804	9.8%
a	134804	9.8%
d	134804	9.8%
F	113780	8.3%
u	113780	8.3%
y	113780	8.3%
P	113780	8.3%
i	113780	8.3%
f	42048	3.1%
Other values (6)	126144	9.2%

addr_state
Categorical

HIGH CORRELATION

Distinct	49
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

CA	21466
NY	11151
TX	10291
FL	8857
IL	5266
Other values (44)	77773

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	269608
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	TX
2nd row	MI
3rd row	CO
4th row	CA
5th row	NC

Value	Count	Frequency (%)
CA	21466	15.9%
NY	11151	8.3%
TX	10291	7.6%
FL	8857	6.6%
IL	5266	3.9%
NJ	5112	3.8%
PA	4599	3.4%
OH	4345	3.2%
GA	4236	3.1%
VA	4097	3.0%
Other values (39)	55384	41.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
ca	21466	15.9%
ny	11151	8.3%
tx	10291	7.6%
fl	8857	6.6%
il	5266	3.9%
nj	5112	3.8%
pa	4599	3.4%
oh	4345	3.2%
ga	4236	3.1%
va	4097	3.0%
Other values (39)	55384	41.1%

Most occurring characters

Value	Count	Frequency (%)
A	48435	18.0%
C	32173	11.9%
N	30114	11.2%
L	17381	6.4%
T	16059	6.0%
M	15081	5.6%
I	13919	5.2%
Y	12723	4.7%
O	12553	4.7%
X	10291	3.8%
Other values (14)	60879	22.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	269608	100.0%

Most frequent character per category

Value	Count	Frequency (%)
A	48435	18.0%
C	32173	11.9%
N	30114	11.2%
L	17381	6.4%
T	16059	6.0%
M	15081	5.6%
I	13919	5.2%
Y	12723	4.7%
O	12553	4.7%
X	10291	3.8%
Other values (14)	60879	22.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	269608	100.0%

Most frequent character per script

Value	Count	Frequency (%)
A	48435	18.0%
C	32173	11.9%
N	30114	11.2%
L	17381	6.4%
T	16059	6.0%
M	15081	5.6%
I	13919	5.2%
Y	12723	4.7%
O	12553	4.7%
X	10291	3.8%
Other values (14)	60879	22.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	269608	100.0%

Most frequent character per block

Value	Count	Frequency (%)
A	48435	18.0%
C	32173	11.9%
N	30114	11.2%
L	17381	6.4%
T	16059	6.0%
M	15081	5.6%
I	13919	5.2%
Y	12723	4.7%
O	12553	4.7%
X	10291	3.8%
Other values (14)	60879	22.6%

annual_inc
Real number (ℝ_≥0)

Distinct	12038
Distinct (%)	8.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	73226.92184
Minimum	6000
Maximum	6100000
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	6000
5-th percentile	30000
Q1	45570.25
median	64000
Q3	89000
95-th percentile	148000
Maximum	6100000
Range	6094000
Interquartile range (IQR)	43429.75

Descriptive statistics

Standard deviation	48822.61326
Coefficient of variation (CV)	0.6667303777
Kurtosis	1808.506083
Mean	73226.92184
Median Absolute Deviation (MAD)	20133.5
Skewness	18.85340526
Sum	9871281971
Variance	2383647565
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60000	5178	3.8%
50000	4817	3.6%
65000	3859	2.9%
70000	3711	2.8%
40000	3707	2.7%
80000	3574	2.7%
45000	3501	2.6%
75000	3400	2.5%
55000	3370	2.5%
90000	2648	2.0%
Other values (12028)	97039	72.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6000	1	< 0.1%
7000	1	< 0.1%
7200	1	< 0.1%
7500	1	< 0.1%
7600	1	< 0.1%

Value	Count	Frequency (%)
6100000	1	< 0.1%
2000000	2	< 0.1%
1510000	1	< 0.1%
1350000	1	< 0.1%
1300000	1	< 0.1%

application_type
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

Individual	134804

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	1348040
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Individual
2nd row	Individual
3rd row	Individual
4th row	Individual
5th row	Individual

Value	Count	Frequency (%)
Individual	134804	100.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
individual	134804	100.0%

Most occurring characters

Value	Count	Frequency (%)
d	269608	20.0%
i	269608	20.0%
I	134804	10.0%
n	134804	10.0%
v	134804	10.0%
u	134804	10.0%
a	134804	10.0%
l	134804	10.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1213236	90.0%
Uppercase Letter	134804	10.0%

Most frequent character per category

Value	Count	Frequency (%)
d	269608	22.2%
i	269608	22.2%
n	134804	11.1%
v	134804	11.1%
u	134804	11.1%
a	134804	11.1%
l	134804	11.1%

Value	Count	Frequency (%)
I	134804	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1348040	100.0%

Most frequent character per script

Value	Count	Frequency (%)
d	269608	20.0%
i	269608	20.0%
I	134804	10.0%
n	134804	10.0%
v	134804	10.0%
u	134804	10.0%
a	134804	10.0%
l	134804	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1348040	100.0%

Most frequent character per block

Value	Count	Frequency (%)
d	269608	20.0%
i	269608	20.0%
I	134804	10.0%
n	134804	10.0%
v	134804	10.0%
u	134804	10.0%
a	134804	10.0%
l	134804	10.0%

desc
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	48034
Distinct (%)	98.6%
Missing	86076
Missing (%)	63.9%
Memory size	1.0 MiB

Borrower added on 01/14/13 > Debt consolidation<br>	6
Borrower added on 07/25/13 > Debt consolidation<br>	6
Borrower added on 12/10/13 > Debt consolidation<br>	5
Borrower added on 12/13/13 > Debt consolidation<br>	5
Borrower added on 08/19/13 > Debt consolidation.<br>	5
Other values (48029)	48701

Length

Max length	2365
Median length	134
Mean length	167.0350312
Min length	1

Characters and Unicode

Total characters	8139283
Distinct characters	92
Distinct categories	13 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	47558 ?
Unique (%)	97.6%

Sample

1st row	Borrower added on 12/31/13 > Bought a new house, furniture, water softener, a second car, etc. Got our lives started and now a manageable monthly payment will help keep them going!<br>
2nd row	Borrower added on 12/31/13 > Combining high interest credit cards to lower interest rate.<br>
3rd row	Borrower added on 12/31/13 > I would like to use this money to payoff existing credit card debt and use the remaining about to purchase a used car that is fuel efficient.<br>
4th row	Borrower added on 12/31/13 > I had some water main break and sewer replacement that ran up my Credit cards. I want to consolidate the Credit cards pay off one loan and refurbish my bathrooms.<br><br> Borrower added on 12/31/13 > I had two water main breaks one sewer and one clean water and the cost ran up credit cards expenditures. I want to consolidate the credit cards with a set payment and upgrade my two bathrooms and water heater.<br><br> Borrower added on 12/31/13 > Consolidate credet cards and upgrade bathrooms.<br><br> Borrower added on 12/31/13 > Consolidate credit cards and upgrade two bathrooms.I have been at this job for six years and the job before this one for 24 years. This will make my finances easier to manage. It will provide more efficient bathroom equipment and water heater.<br>
5th row	Borrower added on 12/31/13 > While being in college there were expenses that I had to make. At the moment it seemed easy to buy thing on credit, but now that I'm full-time employee paying all credit cards seem impossible and it'll be great to make one consolidated payment to one firm with knowing its for a set amount of months.<br>

Value	Count	Frequency (%)
Borrower added on 01/14/13 > Debt consolidation<br>	6	< 0.1%
Borrower added on 07/25/13 > Debt consolidation<br>	6	< 0.1%
Borrower added on 12/10/13 > Debt consolidation<br>	5	< 0.1%
Borrower added on 12/13/13 > Debt consolidation<br>	5	< 0.1%
Borrower added on 08/19/13 > Debt consolidation.<br>	5	< 0.1%
Borrower added on 09/04/13 > debt consolidation<br>	5	< 0.1%
Borrower added on 11/14/13 > Debt consolidation<br>	5	< 0.1%
Borrower added on 09/05/13 > Debt consolidation<br>	5	< 0.1%
Borrower added on 08/06/13 > debt consolidation<br>	5	< 0.1%
Borrower added on 09/19/13 > Debt consolidation<br>	5	< 0.1%
Other values (48024)	48676	36.1%
(Missing)	86076	63.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
on	64032	4.4%
to	61174	4.2%
	56295	3.9%
borrower	55007	3.8%
added	54788	3.8%
i	42636	3.0%
and	36536	2.5%
credit	34996	2.4%
my	34764	2.4%
a	27956	1.9%
Other values (25565)	973787	67.5%

Most occurring characters

Value	Count	Frequency (%)
	1507262	18.5%
e	636955	7.8%
o	568046	7.0%
r	495087	6.1%
a	479295	5.9%
t	428072	5.3%
n	404833	5.0%
d	403289	5.0%
i	320468	3.9%
s	248782	3.1%
Other values (82)	2647194	32.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5610117	68.9%
Space Separator	1507262	18.5%
Decimal Number	368773	4.5%
Uppercase Letter	243704	3.0%
Other Punctuation	219577	2.7%
Math Symbol	180486	2.2%
Currency Symbol	3219	< 0.1%
Dash Punctuation	2944	< 0.1%
Close Punctuation	1656	< 0.1%
Open Punctuation	1518	< 0.1%
Other values (3)	27	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
B	57534	23.6%
I	51933	21.3%
T	24654	10.1%
C	14243	5.8%
A	10262	4.2%
D	7825	3.2%
E	7619	3.1%
L	7437	3.1%
P	7299	3.0%
O	7224	3.0%
Other values (16)	47674	19.6%

Value	Count	Frequency (%)
e	636955	11.4%
o	568046	10.1%
r	495087	8.8%
a	479295	8.5%
t	428072	7.6%
n	404833	7.2%
d	403289	7.2%
i	320468	5.7%
s	248782	4.4%
l	228637	4.1%
Other values (16)	1396653	24.9%

Value	Count	Frequency (%)
/	110948	50.5%
.	72459	33.0%
,	18796	8.6%
'	6354	2.9%
!	4975	2.3%
%	2089	1.0%
;	1897	0.9%
&	1507	0.7%
:	454	0.2%
?	48	< 0.1%
Other values (2)	50	< 0.1%

Value	Count	Frequency (%)
1	109814	29.8%
0	78784	21.4%
3	69865	18.9%
2	39840	10.8%
5	13050	3.5%
4	11959	3.2%
6	11914	3.2%
7	11632	3.2%
9	11631	3.2%
8	10284	2.8%

Value	Count	Frequency (%)
>	117398	65.0%
<	62704	34.7%
+	284	0.2%
~	73	< 0.1%
\|	18	< 0.1%
=	9	< 0.1%

Value	Count	Frequency (%)
(	1511	99.5%
[	6	0.4%
{	1	0.1%

Value	Count	Frequency (%)
)	1649	99.6%
]	6	0.4%
}	1	0.1%

Value	Count	Frequency (%)
	1507262	100.0%

Value	Count	Frequency (%)
-	2944	100.0%

Value	Count	Frequency (%)
$	3219	100.0%

Value	Count	Frequency (%)
_	2	100.0%

Value	Count	Frequency (%)
`	4	100.0%

Value	Count	Frequency (%)
	21	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5853821	71.9%
Common	2285462	28.1%

Most frequent character per script

Value	Count	Frequency (%)
e	636955	10.9%
o	568046	9.7%
r	495087	8.5%
a	479295	8.2%
t	428072	7.3%
n	404833	6.9%
d	403289	6.9%
i	320468	5.5%
s	248782	4.2%
l	228637	3.9%
Other values (42)	1640357	28.0%

Value	Count	Frequency (%)
	1507262	65.9%
>	117398	5.1%
/	110948	4.9%
1	109814	4.8%
0	78784	3.4%
.	72459	3.2%
3	69865	3.1%
<	62704	2.7%
2	39840	1.7%
,	18796	0.8%
Other values (30)	97592	4.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8139283	100.0%

Most frequent character per block

Value	Count	Frequency (%)
	1507262	18.5%
e	636955	7.8%
o	568046	7.0%
r	495087	6.1%
a	479295	5.9%
t	428072	5.3%
n	404833	5.0%
d	403289	5.0%
i	320468	3.9%
s	248782	3.1%
Other values (82)	2647194	32.5%

dti
Real number (ℝ_≥0)

Distinct	3495
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	17.21772358
Minimum	0
Maximum	34.99
Zeros	44
Zeros (%)	< 0.1%
Memory size	1.0 MiB

Quantile statistics

Minimum	0
5-th percentile	5.22
Q1	11.47
median	16.89
Q3	22.8
95-th percentile	30.17
Maximum	34.99
Range	34.99
Interquartile range (IQR)	11.33

Descriptive statistics

Standard deviation	7.595662054
Coefficient of variation (CV)	0.4411536762
Kurtosis	-0.6889768515
Mean	17.21772358
Median Absolute Deviation (MAD)	5.65
Skewness	0.1347048849
Sum	2321018.01
Variance	57.69408204
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
14.4	149	0.1%
18	110	0.1%
15.6	104	0.1%
16.8	103	0.1%
19.2	102	0.1%
20.4	100	0.1%
21.6	98	0.1%
12.72	98	0.1%
13.2	98	0.1%
12	97	0.1%
Other values (3485)	133745	99.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	44	< 0.1%
0.01	2	< 0.1%
0.02	1	< 0.1%
0.03	1	< 0.1%
0.06	2	< 0.1%

Value	Count	Frequency (%)
34.99	8	< 0.1%
34.98	11	< 0.1%
34.97	11	< 0.1%
34.96	10	< 0.1%
34.95	11	< 0.1%

earliest_cr_line
Categorical

HIGH CARDINALITY

Distinct	607
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

Oct-2000	1122
Oct-2001	1065
Oct-1999	1033
Nov-1999	1026
Nov-2000	1015
Other values (602)	129543

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	1078432
Distinct characters	33
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	40 ?
Unique (%)	< 0.1%

Sample

1st row	Sep-2003
2nd row	Oct-1986
3rd row	Nov-1997
4th row	Nov-1994
5th row	Dec-2009

Value	Count	Frequency (%)
Oct-2000	1122	0.8%
Oct-2001	1065	0.8%
Oct-1999	1033	0.8%
Nov-1999	1026	0.8%
Nov-2000	1015	0.8%
Dec-2000	1007	0.7%
Aug-2000	970	0.7%
Nov-1998	948	0.7%
Jan-2001	944	0.7%
Dec-1999	942	0.7%
Other values (597)	124732	92.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
oct-2000	1122	0.8%
oct-2001	1065	0.8%
oct-1999	1033	0.8%
nov-1999	1026	0.8%
nov-2000	1015	0.8%
dec-2000	1007	0.7%
aug-2000	970	0.7%
nov-1998	948	0.7%
jan-2001	944	0.7%
dec-1999	942	0.7%
Other values (597)	124732	92.5%

Most occurring characters

Value	Count	Frequency (%)
9	148900	13.8%
-	134804	12.5%
0	131115	12.2%
1	91159	8.5%
2	70922	6.6%
e	34512	3.2%
u	32812	3.0%
J	32753	3.0%
a	32582	3.0%
8	28932	2.7%
Other values (23)	339941	31.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	539216	50.0%
Lowercase Letter	269608	25.0%
Uppercase Letter	134804	12.5%
Dash Punctuation	134804	12.5%

Most frequent character per category

Value	Count	Frequency (%)
e	34512	12.8%
u	32812	12.2%
a	32582	12.1%
c	25523	9.5%
n	22009	8.2%
p	21363	7.9%
r	20121	7.5%
t	13070	4.8%
o	12258	4.5%
v	12258	4.5%
Other values (4)	43100	16.0%

Value	Count	Frequency (%)
9	148900	27.6%
0	131115	24.3%
1	91159	16.9%
2	70922	13.2%
8	28932	5.4%
7	16011	3.0%
6	13880	2.6%
4	12887	2.4%
5	12850	2.4%
3	12560	2.3%

Value	Count	Frequency (%)
J	32753	24.3%
A	21315	15.8%
M	20896	15.5%
O	13070	9.7%
D	12453	9.2%
N	12258	9.1%
S	11793	8.7%
F	10266	7.6%

Value	Count	Frequency (%)
-	134804	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	674020	62.5%
Latin	404412	37.5%

Most frequent character per script

Value	Count	Frequency (%)
e	34512	8.5%
u	32812	8.1%
J	32753	8.1%
a	32582	8.1%
c	25523	6.3%
n	22009	5.4%
p	21363	5.3%
A	21315	5.3%
M	20896	5.2%
r	20121	5.0%
Other values (12)	140526	34.7%

Value	Count	Frequency (%)
9	148900	22.1%
-	134804	20.0%
0	131115	19.5%
1	91159	13.5%
2	70922	10.5%
8	28932	4.3%
7	16011	2.4%
6	13880	2.1%
4	12887	1.9%
5	12850	1.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1078432	100.0%

Most frequent character per block

Value	Count	Frequency (%)
9	148900	13.8%
-	134804	12.5%
0	131115	12.2%
1	91159	8.5%
2	70922	6.6%
e	34512	3.2%
u	32812	3.0%
J	32753	3.0%
a	32582	3.0%
8	28932	2.7%
Other values (23)	339941	31.5%

emp_length
Categorical

HIGH CORRELATION
MISSING

Distinct	11
Distinct (%)	< 0.1%
Missing	5962
Missing (%)	4.4%
Memory size	1.0 MiB

10+ years	45799
2 years	11239
3 years	10095
5 years	9727
< 1 year	9083
Other values (6)	42899

Length

Max length	9
Median length	7
Mean length	7.721030409
Min length	6

Characters and Unicode

Total characters	994793
Distinct characters	18
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3 years
2nd row	10+ years
3rd row	10+ years
4th row	5 years
5th row	4 years

Value	Count	Frequency (%)
10+ years	45799	34.0%
2 years	11239	8.3%
3 years	10095	7.5%
5 years	9727	7.2%
< 1 year	9083	6.7%
6 years	8175	6.1%
7 years	8173	6.1%
1 year	7782	5.8%
4 years	6884	5.1%
8 years	6667	4.9%
(Missing)	5962	4.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
years	111977	42.0%
10	45799	17.2%
1	16865	6.3%
year	16865	6.3%
2	11239	4.2%
3	10095	3.8%
5	9727	3.6%
	9083	3.4%
6	8175	3.1%
7	8173	3.1%
Other values (3)	18769	7.0%

Most occurring characters

Value	Count	Frequency (%)
	137925	13.9%
y	128842	13.0%
e	128842	13.0%
a	128842	13.0%
r	128842	13.0%
s	111977	11.3%
1	62664	6.3%
0	45799	4.6%
+	45799	4.6%
2	11239	1.1%
Other values (8)	64022	6.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	627345	63.1%
Decimal Number	174641	17.6%
Space Separator	137925	13.9%
Math Symbol	54882	5.5%

Most frequent character per category

Value	Count	Frequency (%)
1	62664	35.9%
0	45799	26.2%
2	11239	6.4%
3	10095	5.8%
5	9727	5.6%
6	8175	4.7%
7	8173	4.7%
4	6884	3.9%
8	6667	3.8%
9	5218	3.0%

Value	Count	Frequency (%)
y	128842	20.5%
e	128842	20.5%
a	128842	20.5%
r	128842	20.5%
s	111977	17.8%

Value	Count	Frequency (%)
+	45799	83.4%
<	9083	16.6%

Value	Count	Frequency (%)
	137925	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	627345	63.1%
Common	367448	36.9%

Most frequent character per script

Value	Count	Frequency (%)
	137925	37.5%
1	62664	17.1%
0	45799	12.5%
+	45799	12.5%
2	11239	3.1%
3	10095	2.7%
5	9727	2.6%
<	9083	2.5%
6	8175	2.2%
7	8173	2.2%
Other values (3)	18769	5.1%

Value	Count	Frequency (%)
y	128842	20.5%
e	128842	20.5%
a	128842	20.5%
r	128842	20.5%
s	111977	17.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	994793	100.0%

Most frequent character per block

Value	Count	Frequency (%)
	137925	13.9%
y	128842	13.0%
e	128842	13.0%
a	128842	13.0%
r	128842	13.0%
s	111977	11.3%
1	62664	6.3%
0	45799	4.6%
+	45799	4.6%
2	11239	1.1%
Other values (8)	64022	6.4%

emp_title
Categorical

HIGH CARDINALITY
MISSING

Distinct	83424
Distinct (%)	66.1%
Missing	8565
Missing (%)	6.4%
Memory size	1.0 MiB

Teacher	832
Manager	666
RN	388
Registered Nurse	356
Supervisor	304
Other values (83419)	123693

Length

Max length	42
Median length	17
Mean length	17.57868804
Min length	1

Characters and Unicode

Total characters	2219116
Distinct characters	110
Distinct categories	17 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	73605 ?
Unique (%)	58.3%

Sample

1st row	Systems Engineer
2nd row	Team Leadern Customer Ops & Systems
3rd row	LTC
4th row	Area Sales Manager
5th row	Project Manager

Value	Count	Frequency (%)
Teacher	832	0.6%
Manager	666	0.5%
RN	388	0.3%
Registered Nurse	356	0.3%
Supervisor	304	0.2%
US Army	287	0.2%
Project Manager	256	0.2%
Sales	218	0.2%
Bank of America	216	0.2%
Office Manager	210	0.2%
Other values (83414)	122506	90.9%
(Missing)	8565	6.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
of	8009	2.5%
manager	6757	2.1%
inc	6480	2.1%
	3320	1.1%
center	2493	0.8%
county	2368	0.8%
services	2150	0.7%
school	2115	0.7%
medical	2115	0.7%
hospital	2072	0.7%
Other values (36606)	277255	88.0%

Most occurring characters

Value	Count	Frequency (%)
e	197644	8.9%
	193689	8.7%
a	152294	6.9%
r	147280	6.6%
n	139193	6.3%
i	137010	6.2%
t	129590	5.8%
o	128482	5.8%
s	100848	4.5%
c	80876	3.6%
Other values (100)	812210	36.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1626743	73.3%
Uppercase Letter	371201	16.7%
Space Separator	193689	8.7%
Other Punctuation	21516	1.0%
Decimal Number	2744	0.1%
Dash Punctuation	2431	0.1%
Open Punctuation	359	< 0.1%
Close Punctuation	348	< 0.1%
Math Symbol	48	< 0.1%
Control	21	< 0.1%
Other values (7)	16	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
S	42930	11.6%
C	41268	11.1%
A	30497	8.2%
M	23598	6.4%
I	20835	5.6%
P	20159	5.4%
T	19896	5.4%
E	18411	5.0%
D	17401	4.7%
R	17197	4.6%
Other values (19)	119009	32.1%

Value	Count	Frequency (%)
e	197644	12.1%
a	152294	9.4%
r	147280	9.1%
n	139193	8.6%
i	137010	8.4%
t	129590	8.0%
o	128482	7.9%
s	100848	6.2%
c	80876	5.0%
l	78778	4.8%
Other values (17)	334748	20.6%

Value	Count	Frequency (%)
.	9187	42.7%
,	4977	23.1%
&	3524	16.4%
/	2119	9.8%
'	1545	7.2%
#	73	0.3%
:	22	0.1%
!	17	0.1%
"	14	0.1%
\	13	0.1%
Other values (4)	25	0.1%

Value	Count	Frequency (%)
1	551	20.1%
2	448	16.3%
3	405	14.8%
0	256	9.3%
4	248	9.0%
5	203	7.4%
6	180	6.6%
9	170	6.2%
7	156	5.7%
8	127	4.6%

Value	Count	Frequency (%)
	6	28.6%
	5	23.8%
	2	9.5%
	2	9.5%
	1	4.8%
	1	4.8%
	1	4.8%
	1	4.8%
	1	4.8%
	1	4.8%

Value	Count	Frequency (%)
+	35	72.9%
\|	9	18.8%
~	2	4.2%
¬	1	2.1%
±	1	2.1%

Value	Count	Frequency (%)
(	358	99.7%
[	1	0.3%

Value	Count	Frequency (%)
)	347	99.7%
]	1	0.3%

Value	Count	Frequency (%)
$	3	60.0%
¢	2	40.0%

Value	Count	Frequency (%)
²	1	50.0%
³	1	50.0%

Value	Count	Frequency (%)
	193689	100.0%

Value	Count	Frequency (%)
-	2431	100.0%

Value	Count	Frequency (%)
	1	100.0%

Value	Count	Frequency (%)
`	4	100.0%

Value	Count	Frequency (%)
©	1	100.0%

Value	Count	Frequency (%)
_	2	100.0%

Value	Count	Frequency (%)
«	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1997944	90.0%
Common	221172	10.0%

Most frequent character per script

Value	Count	Frequency (%)
e	197644	9.9%
a	152294	7.6%
r	147280	7.4%
n	139193	7.0%
i	137010	6.9%
t	129590	6.5%
o	128482	6.4%
s	100848	5.0%
c	80876	4.0%
l	78778	3.9%
Other values (46)	705949	35.3%

Value	Count	Frequency (%)
	193689	87.6%
.	9187	4.2%
,	4977	2.3%
&	3524	1.6%
-	2431	1.1%
/	2119	1.0%
'	1545	0.7%
1	551	0.2%
2	448	0.2%
3	405	0.2%
Other values (44)	2296	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2219060	> 99.9%
None	56	< 0.1%

Most frequent character per block

Value	Count	Frequency (%)
e	197644	8.9%
	193689	8.7%
a	152294	6.9%
r	147280	6.6%
n	139193	6.3%
i	137010	6.2%
t	129590	5.8%
o	128482	5.8%
s	100848	4.5%
c	80876	3.6%
Other values (77)	812154	36.6%

Value	Count	Frequency (%)
Ã	13	23.2%
â	6	10.7%
	6	10.7%
	5	8.9%
Â	5	8.9%
	2	3.6%
¢	2	3.6%
	2	3.6%
	1	1.8%
©	1	1.8%
Other values (13)	13	23.2%

fico_range_high
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	38
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	698.9989763
Minimum	664
Maximum	850
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	664
5-th percentile	664
Q1	679
median	694
Q3	714
95-th percentile	754
Maximum	850
Range	186
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	28.76356342
Coefficient of variation (CV)	0.04114965027
Kurtosis	2.448939714
Mean	698.9989763
Median Absolute Deviation (MAD)	15
Skewness	1.372036164
Sum	94227858
Variance	827.3425803
Monotocity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
674	11378	8.4%
684	11205	8.3%
679	10601	7.9%
669	10512	7.8%
694	10319	7.7%
689	10213	7.6%
664	9642	7.2%
699	9449	7.0%
704	8416	6.2%
709	7605	5.6%
Other values (28)	35464	26.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
664	9642	7.2%
669	10512	7.8%
674	11378	8.4%
679	10601	7.9%
684	11205	8.3%

Value	Count	Frequency (%)
850	12	< 0.1%
844	19	< 0.1%
839	24	< 0.1%
834	56	< 0.1%
829	86	0.1%

fico_range_low
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	38
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	694.9988873
Minimum	660
Maximum	845
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	660
5-th percentile	660
Q1	675
median	690
Q3	710
95-th percentile	750
Maximum	845
Range	185
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	28.76309763
Coefficient of variation (CV)	0.04138581825
Kurtosis	2.447536123
Mean	694.9988873
Median Absolute Deviation (MAD)	15
Skewness	1.3718579
Sum	93688630
Variance	827.3157855
Monotocity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
670	11378	8.4%
680	11205	8.3%
675	10601	7.9%
665	10512	7.8%
690	10319	7.7%
685	10213	7.6%
660	9642	7.2%
695	9449	7.0%
700	8416	6.2%
705	7605	5.6%
Other values (28)	35464	26.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
660	9642	7.2%
665	10512	7.8%
670	11378	8.4%
675	10601	7.9%
680	11205	8.3%

Value	Count	Frequency (%)
845	12	< 0.1%
840	19	< 0.1%
835	24	< 0.1%
830	56	< 0.1%
825	86	0.1%

grade
Categorical

HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

B	44115
C	38130
D	20566
A	17679
E	9059
Other values (2)	5255

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	134804
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A
2nd row	B
3rd row	B
4th row	A
5th row	B

Value	Count	Frequency (%)
B	44115	32.7%
C	38130	28.3%
D	20566	15.3%
A	17679	13.1%
E	9059	6.7%
F	4392	3.3%
G	863	0.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
b	44115	32.7%
c	38130	28.3%
d	20566	15.3%
a	17679	13.1%
e	9059	6.7%
f	4392	3.3%
g	863	0.6%

Most occurring characters

Value	Count	Frequency (%)
B	44115	32.7%
C	38130	28.3%
D	20566	15.3%
A	17679	13.1%
E	9059	6.7%
F	4392	3.3%
G	863	0.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	134804	100.0%

Most frequent character per category

Value	Count	Frequency (%)
B	44115	32.7%
C	38130	28.3%
D	20566	15.3%
A	17679	13.1%
E	9059	6.7%
F	4392	3.3%
G	863	0.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	134804	100.0%

Most frequent character per script

Value	Count	Frequency (%)
B	44115	32.7%
C	38130	28.3%
D	20566	15.3%
A	17679	13.1%
E	9059	6.7%
F	4392	3.3%
G	863	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	134804	100.0%

Most frequent character per block

Value	Count	Frequency (%)
B	44115	32.7%
C	38130	28.3%
D	20566	15.3%
A	17679	13.1%
E	9059	6.7%
F	4392	3.3%
G	863	0.6%

home_ownership
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

MORTGAGE	72061
RENT	51495
OWN	11248

Length

Max length	8
Median length	8
Mean length	6.054805495
Min length	3

Characters and Unicode

Total characters	816212
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	MORTGAGE
2nd row	OWN
3rd row	MORTGAGE
4th row	MORTGAGE
5th row	RENT

Value	Count	Frequency (%)
MORTGAGE	72061	53.5%
RENT	51495	38.2%
OWN	11248	8.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
mortgage	72061	53.5%
rent	51495	38.2%
own	11248	8.3%

Most occurring characters

Value	Count	Frequency (%)
G	144122	17.7%
R	123556	15.1%
T	123556	15.1%
E	123556	15.1%
O	83309	10.2%
M	72061	8.8%
A	72061	8.8%
N	62743	7.7%
W	11248	1.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	816212	100.0%

Most frequent character per category

Value	Count	Frequency (%)
G	144122	17.7%
R	123556	15.1%
T	123556	15.1%
E	123556	15.1%
O	83309	10.2%
M	72061	8.8%
A	72061	8.8%
N	62743	7.7%
W	11248	1.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	816212	100.0%

Most frequent character per script

Value	Count	Frequency (%)
G	144122	17.7%
R	123556	15.1%
T	123556	15.1%
E	123556	15.1%
O	83309	10.2%
M	72061	8.8%
A	72061	8.8%
N	62743	7.7%
W	11248	1.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	816212	100.0%

Most frequent character per block

Value	Count	Frequency (%)
G	144122	17.7%
R	123556	15.1%
T	123556	15.1%
E	123556	15.1%
O	83309	10.2%
M	72061	8.8%
A	72061	8.8%
N	62743	7.7%
W	11248	1.4%

initial_list_status
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

f	98892
w	35912

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	134804
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	f
2nd row	w
3rd row	f
4th row	w
5th row	f

Value	Count	Frequency (%)
f	98892	73.4%
w	35912	26.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
f	98892	73.4%
w	35912	26.6%

Most occurring characters

Value	Count	Frequency (%)
f	98892	73.4%
w	35912	26.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	134804	100.0%

Most frequent character per category

Value	Count	Frequency (%)
f	98892	73.4%
w	35912	26.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	134804	100.0%

Most frequent character per script

Value	Count	Frequency (%)
f	98892	73.4%
w	35912	26.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	134804	100.0%

Most frequent character per block

Value	Count	Frequency (%)
f	98892	73.4%
w	35912	26.6%

installment
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	24312
Distinct (%)	18.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	452.3941477
Minimum	4.93
Maximum	1408.13
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	4.93
5-th percentile	132.84
Q1	280.82
median	404.3
Q3	587.34
95-th percentile	921.85
Maximum	1408.13
Range	1403.2
Interquartile range (IQR)	306.52

Descriptive statistics

Standard deviation	240.7709287
Coefficient of variation (CV)	0.5322149502
Kurtosis	0.7583653277
Mean	452.3941477
Median Absolute Deviation (MAD)	145.66
Skewness	0.9037179921
Sum	60984540.68
Variance	57970.64013
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
337.47	403	0.3%
635.07	378	0.3%
317.54	372	0.3%
332.72	371	0.3%
343.39	359	0.3%
328.06	357	0.3%
332.1	351	0.3%
476.3	308	0.2%
625.81	303	0.2%
492.08	301	0.2%
Other values (24302)	131301	97.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4.93	1	< 0.1%
23.26	1	< 0.1%
25.86	1	< 0.1%
27.85	1	< 0.1%
28.82	2	< 0.1%

Value	Count	Frequency (%)
1408.13	1	< 0.1%
1407.01	1	< 0.1%
1406.45	4	< 0.1%
1402.17	2	< 0.1%
1396.79	1	< 0.1%

int_rate
Real number (ℝ_≥0)

Distinct	100
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	14.53162777
Minimum	6
Maximum	26.06
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	6
5-th percentile	7.62
Q1	11.14
median	14.33
Q3	17.56
95-th percentile	22.47
Maximum	26.06
Range	20.06
Interquartile range (IQR)	6.42

Descriptive statistics

Standard deviation	4.437451623
Coefficient of variation (CV)	0.3053650763
Kurtosis	-0.4702868643
Mean	14.53162777
Median Absolute Deviation (MAD)	3.19
Skewness	0.2424329856
Sum	1958921.55
Variance	19.69097691
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8.9	5001	3.7%
14.33	4872	3.6%
13.11	4647	3.4%
12.12	4445	3.3%
11.14	4292	3.2%
7.9	3444	2.6%
15.8	3425	2.5%
11.99	3384	2.5%
16.29	3265	2.4%
10.99	3185	2.4%
Other values (90)	94844	70.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6	29	< 0.1%
6.03	2569	1.9%
6.62	2144	1.6%
6.97	397	0.3%
7.62	3155	2.3%

Value	Count	Frequency (%)
26.06	52	< 0.1%
25.99	62	< 0.1%
25.89	123	0.1%
25.83	149	0.1%
25.8	188	0.1%

issue_d
Categorical

HIGH CORRELATION

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

Dec-2013	15012
Nov-2013	14720
Oct-2013	14127
Sep-2013	12987
Aug-2013	12674
Other values (7)	65284

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	1078432
Distinct characters	27
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Dec-2013
2nd row	Dec-2013
3rd row	Dec-2013
4th row	Dec-2013
5th row	Dec-2013

Value	Count	Frequency (%)
Dec-2013	15012	11.1%
Nov-2013	14720	10.9%
Oct-2013	14127	10.5%
Sep-2013	12987	9.6%
Aug-2013	12674	9.4%
Jul-2013	11910	8.8%
Jun-2013	10899	8.1%
May-2013	10350	7.7%
Apr-2013	9419	7.0%
Mar-2013	8273	6.1%
Other values (2)	14433	10.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
dec-2013	15012	11.1%
nov-2013	14720	10.9%
oct-2013	14127	10.5%
sep-2013	12987	9.6%
aug-2013	12674	9.4%
jul-2013	11910	8.8%
jun-2013	10899	8.1%
may-2013	10350	7.7%
apr-2013	9419	7.0%
mar-2013	8273	6.1%
Other values (2)	14433	10.7%

Most occurring characters

Value	Count	Frequency (%)
-	134804	12.5%
2	134804	12.5%
0	134804	12.5%
1	134804	12.5%
3	134804	12.5%
e	35560	3.3%
u	35483	3.3%
J	29681	2.8%
c	29139	2.7%
a	25495	2.4%
Other values (17)	249054	23.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	539216	50.0%
Lowercase Letter	269608	25.0%
Uppercase Letter	134804	12.5%
Dash Punctuation	134804	12.5%

Most frequent character per category

Value	Count	Frequency (%)
e	35560	13.2%
u	35483	13.2%
c	29139	10.8%
a	25495	9.5%
p	22406	8.3%
n	17771	6.6%
r	17692	6.6%
o	14720	5.5%
v	14720	5.5%
t	14127	5.2%
Other values (4)	42495	15.8%

Value	Count	Frequency (%)
J	29681	22.0%
A	22093	16.4%
M	18623	13.8%
D	15012	11.1%
N	14720	10.9%
O	14127	10.5%
S	12987	9.6%
F	7561	5.6%

Value	Count	Frequency (%)
2	134804	25.0%
0	134804	25.0%
1	134804	25.0%
3	134804	25.0%

Value	Count	Frequency (%)
-	134804	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	674020	62.5%
Latin	404412	37.5%

Most frequent character per script

Value	Count	Frequency (%)
e	35560	8.8%
u	35483	8.8%
J	29681	7.3%
c	29139	7.2%
a	25495	6.3%
p	22406	5.5%
A	22093	5.5%
M	18623	4.6%
n	17771	4.4%
r	17692	4.4%
Other values (12)	150469	37.2%

Value	Count	Frequency (%)
-	134804	20.0%
2	134804	20.0%
0	134804	20.0%
1	134804	20.0%
3	134804	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1078432	100.0%

Most frequent character per block

Value	Count	Frequency (%)
-	134804	12.5%
2	134804	12.5%
0	134804	12.5%
1	134804	12.5%
3	134804	12.5%
e	35560	3.3%
u	35483	3.3%
J	29681	2.8%
c	29139	2.7%
a	25495	2.4%
Other values (17)	249054	23.1%

loan_amnt
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	1221
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	14707.37515
Minimum	1000
Maximum	35000
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	1000
5-th percentile	4000
Q1	8500
median	13000
Q3	20000
95-th percentile	30000
Maximum	35000
Range	34000
Interquartile range (IQR)	11500

Descriptive statistics

Standard deviation	8098.737341
Coefficient of variation (CV)	0.5506582417
Kurtosis	-0.198448233
Mean	14707.37515
Median Absolute Deviation (MAD)	5250
Skewness	0.6617993948
Sum	1982613000
Variance	65589546.52
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	9836	7.3%
12000	7244	5.4%
15000	7046	5.2%
20000	6873	5.1%
8000	4401	3.3%
35000	4317	3.2%
16000	4019	3.0%
18000	3699	2.7%
24000	3547	2.6%
6000	3402	2.5%
Other values (1211)	80420	59.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1000	349	0.3%
1025	2	< 0.1%
1075	1	< 0.1%
1100	7	< 0.1%
1125	3	< 0.1%

Value	Count	Frequency (%)
35000	4317	3.2%
34975	6	< 0.1%
34925	1	< 0.1%
34900	1	< 0.1%
34825	1	< 0.1%

mort_acc
Real number (ℝ_≥0)

ZEROS

Distinct	29
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.878082253
Minimum	0
Maximum	31
Zeros	51653
Zeros (%)	38.3%
Memory size	1.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	3
95-th percentile	6
Maximum	31
Range	31
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.19635659
Coefficient of variation (CV)	1.16946773
Kurtosis	3.580126873
Mean	1.878082253
Median Absolute Deviation (MAD)	1
Skewness	1.503936043
Sum	253173
Variance	4.823982269
Monotocity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
0	51653	38.3%
1	22560	16.7%
2	18408	13.7%
3	14164	10.5%
4	10808	8.0%
5	7254	5.4%
6	4453	3.3%
7	2556	1.9%
8	1393	1.0%
9	736	0.5%
Other values (19)	819	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	51653	38.3%
1	22560	16.7%
2	18408	13.7%
3	14164	10.5%
4	10808	8.0%

Value	Count	Frequency (%)
31	1	< 0.1%
30	1	< 0.1%
29	1	< 0.1%
27	1	< 0.1%
25	1	< 0.1%

open_acc
Real number (ℝ_≥0)

Distinct	54
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	11.15063351
Minimum	0
Maximum	62
Zeros	3
Zeros (%)	< 0.1%
Memory size	1.0 MiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	8
median	10
Q3	14
95-th percentile	20
Maximum	62
Range	62
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.652662916
Coefficient of variation (CV)	0.417255478
Kurtosis	2.077010565
Mean	11.15063351
Median Absolute Deviation (MAD)	3
Skewness	1.017473472
Sum	1503150
Variance	21.64727221
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9	13379	9.9%
10	12949	9.6%
8	12384	9.2%
11	11971	8.9%
7	10902	8.1%
12	10484	7.8%
13	8780	6.5%
6	8506	6.3%
14	7484	5.6%
15	6034	4.5%
Other values (44)	31931	23.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	3	< 0.1%
1	41	< 0.1%
2	340	0.3%
3	1114	0.8%
4	3000	2.2%

Value	Count	Frequency (%)
62	1	< 0.1%
53	2	< 0.1%
52	1	< 0.1%
51	1	< 0.1%
50	2	< 0.1%

pub_rec
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	14
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.1368060295
Minimum	0
Maximum	54
Zeros	118805
Zeros (%)	88.1%
Memory size	1.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	54
Range	54
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4632517901
Coefficient of variation (CV)	3.386194248
Kurtosis	2305.686782
Mean	0.1368060295
Median Absolute Deviation (MAD)	0
Skewness	24.06241939
Sum	18442
Variance	0.214602221
Monotocity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
0	118805	88.1%
1	14477	10.7%
2	1071	0.8%
3	261	0.2%
4	96	0.1%
5	44	< 0.1%
6	24	< 0.1%
7	13	< 0.1%
8	6	< 0.1%
11	2	< 0.1%
Other values (4)	5	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	118805	88.1%
1	14477	10.7%
2	1071	0.8%
3	261	0.2%
4	96	0.1%

Value	Count	Frequency (%)
54	1	< 0.1%
49	1	< 0.1%
11	2	< 0.1%
10	1	< 0.1%
9	2	< 0.1%

pub_rec_bankruptcies
Real number (ℝ_≥0)

ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.1092326637
Minimum	0
Maximum	8
Zeros	120491
Zeros (%)	89.4%
Memory size	1.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3258204726
Coefficient of variation (CV)	2.982811748
Kurtosis	17.5811771
Mean	0.1092326637
Median Absolute Deviation (MAD)	0
Skewness	3.281809345
Sum	14725
Variance	0.1061589803
Monotocity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	120491	89.4%
1	14010	10.4%
2	239	0.2%
3	37	< 0.1%
4	18	< 0.1%
6	4	< 0.1%
5	3	< 0.1%
7	1	< 0.1%
8	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	120491	89.4%
1	14010	10.4%
2	239	0.2%
3	37	< 0.1%
4	18	< 0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	1	< 0.1%
6	4	< 0.1%
5	3	< 0.1%
4	18	< 0.1%

purpose
Categorical

HIGH CORRELATION

Distinct	13
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

debt_consolidation	80634
credit_card	32804
home_improvement	7403
other	5842
major_purchase	2298
Other values (8)	5823

Length

Max length	18
Median length	18
Mean length	15.11227412
Min length	3

Characters and Unicode

Total characters	2037195
Distinct characters	22
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	debt_consolidation
2nd row	debt_consolidation
3rd row	debt_consolidation
4th row	debt_consolidation
5th row	debt_consolidation

Value	Count	Frequency (%)
debt_consolidation	80634	59.8%
credit_card	32804	24.3%
home_improvement	7403	5.5%
other	5842	4.3%
major_purchase	2298	1.7%
small_business	1359	1.0%
car	1050	0.8%
medical	889	0.7%
house	675	0.5%
moving	639	0.5%
Other values (3)	1211	0.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
debt_consolidation	80634	59.8%
credit_card	32804	24.3%
home_improvement	7403	5.5%
other	5842	4.3%
major_purchase	2298	1.7%
small_business	1359	1.0%
car	1050	0.8%
medical	889	0.7%
house	675	0.5%
moving	639	0.5%
Other values (3)	1211	0.9%

Most occurring characters

Value	Count	Frequency (%)
o	266727	13.1%
d	228955	11.2%
t	207882	10.2%
i	205522	10.1%
n	171931	8.4%
c	151044	7.4%
e	147560	7.2%
_	124549	6.1%
a	122513	6.0%
s	89043	4.4%
Other values (12)	321469	15.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1912646	93.9%
Connector Punctuation	124549	6.1%

Most frequent character per category

Value	Count	Frequency (%)
o	266727	13.9%
d	228955	12.0%
t	207882	10.9%
i	205522	10.7%
n	171931	9.0%
c	151044	7.9%
e	147560	7.7%
a	122513	6.4%
s	89043	4.7%
r	84601	4.4%
Other values (11)	236868	12.4%

Value	Count	Frequency (%)
_	124549	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1912646	93.9%
Common	124549	6.1%

Most frequent character per script

Value	Count	Frequency (%)
o	266727	13.9%
d	228955	12.0%
t	207882	10.9%
i	205522	10.7%
n	171931	9.0%
c	151044	7.9%
e	147560	7.7%
a	122513	6.4%
s	89043	4.7%
r	84601	4.4%
Other values (11)	236868	12.4%

Value	Count	Frequency (%)
_	124549	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2037195	100.0%

Most frequent character per block

Value	Count	Frequency (%)
o	266727	13.1%
d	228955	11.2%
t	207882	10.2%
i	205522	10.1%
n	171931	8.4%
c	151044	7.4%
e	147560	7.2%
_	124549	6.1%
a	122513	6.0%
s	89043	4.4%
Other values (12)	321469	15.8%

revol_bal
Real number (ℝ_≥0)

SKEWED

Distinct	39861
Distinct (%)	29.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	16800.48039
Minimum	0
Maximum	2568995
Zeros	334
Zeros (%)	0.2%
Memory size	1.0 MiB

Quantile statistics

Minimum	0
5-th percentile	2964.3
Q1	7325
median	12692
Q3	21121
95-th percentile	38914.85
Maximum	2568995
Range	2568995
Interquartile range (IQR)	13796

Descriptive statistics

Standard deviation	20785.56609
Coefficient of variation (CV)	1.2372007
Kurtosis	2477.081979
Mean	16800.48039
Median Absolute Deviation (MAD)	6305
Skewness	27.9368739
Sum	2264771958
Variance	432039757.8
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	334	0.2%
7429	21	< 0.1%
5655	17	< 0.1%
8881	17	< 0.1%
6852	16	< 0.1%
9334	16	< 0.1%
8979	16	< 0.1%
11363	16	< 0.1%
9529	16	< 0.1%
8775	16	< 0.1%
Other values (39851)	134319	99.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	334	0.2%
1	4	< 0.1%
2	7	< 0.1%
3	7	< 0.1%
4	7	< 0.1%

Value	Count	Frequency (%)
2568995	1	< 0.1%
1746716	1	< 0.1%
1743266	1	< 0.1%
694615	1	< 0.1%
617838	1	< 0.1%

revol_util
Real number (ℝ_≥0)

Distinct	1068
Distinct (%)	0.8%
Missing	78
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%

Mean	58.58012113
Minimum	0
Maximum	140.4
Zeros	350
Zeros (%)	0.3%
Memory size	1.0 MiB

Quantile statistics

Minimum	0
5-th percentile	18.4
Q1	42.8
median	60.3
Q3	76.2
95-th percentile	92.3
Maximum	140.4
Range	140.4
Interquartile range (IQR)	33.4

Descriptive statistics

Standard deviation	22.50388896
Coefficient of variation (CV)	0.384155726
Kurtosis	-0.5385026014
Mean	58.58012113
Median Absolute Deviation (MAD)	16.6
Skewness	-0.3455529303
Sum	7892265.4
Variance	506.4250184
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	350	0.3%
64.6	256	0.2%
59.3	252	0.2%
70.8	252	0.2%
67.4	251	0.2%
61.5	250	0.2%
72	250	0.2%
68.7	248	0.2%
61.6	248	0.2%
71.8	247	0.2%
Other values (1058)	132122	98.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	350	0.3%
0.1	37	< 0.1%
0.2	46	< 0.1%
0.3	29	< 0.1%
0.4	31	< 0.1%

Value	Count	Frequency (%)
140.4	1	< 0.1%
128.1	1	< 0.1%
127.6	1	< 0.1%
122.5	1	< 0.1%
120.2	2	< 0.1%

sub_grade
Categorical

HIGH CORRELATION

Distinct	35
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

B4	10570
B3	10289
B2	9793
C3	8172
C4	7864
Other values (30)	88116

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	269608
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A3
2nd row	B2
3rd row	B3
4th row	A3
5th row	B2

Value	Count	Frequency (%)
B4	10570	7.8%
B3	10289	7.6%
B2	9793	7.3%
C3	8172	6.1%
C4	7864	5.8%
B1	7822	5.8%
C1	7646	5.7%
C2	7313	5.4%
C5	7135	5.3%
B5	5641	4.2%
Other values (25)	52559	39.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
b4	10570	7.8%
b3	10289	7.6%
b2	9793	7.3%
c3	8172	6.1%
c4	7864	5.8%
b1	7822	5.8%
c1	7646	5.7%
c2	7313	5.4%
c5	7135	5.3%
b5	5641	4.2%
Other values (25)	52559	39.0%

Most occurring characters

Value	Count	Frequency (%)
B	44115	16.4%
C	38130	14.1%
4	28554	10.6%
3	28160	10.4%
2	27478	10.2%
1	26970	10.0%
5	23642	8.8%
D	20566	7.6%
A	17679	6.6%
E	9059	3.4%
Other values (2)	5255	1.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	134804	50.0%
Decimal Number	134804	50.0%

Most frequent character per category

Value	Count	Frequency (%)
B	44115	32.7%
C	38130	28.3%
D	20566	15.3%
A	17679	13.1%
E	9059	6.7%
F	4392	3.3%
G	863	0.6%

Value	Count	Frequency (%)
4	28554	21.2%
3	28160	20.9%
2	27478	20.4%
1	26970	20.0%
5	23642	17.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	134804	50.0%
Common	134804	50.0%

Most frequent character per script

Value	Count	Frequency (%)
B	44115	32.7%
C	38130	28.3%
D	20566	15.3%
A	17679	13.1%
E	9059	6.7%
F	4392	3.3%
G	863	0.6%

Value	Count	Frequency (%)
4	28554	21.2%
3	28160	20.9%
2	27478	20.4%
1	26970	20.0%
5	23642	17.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	269608	100.0%

Most frequent character per block

Value	Count	Frequency (%)
B	44115	16.4%
C	38130	14.1%
4	28554	10.6%
3	28160	10.4%
2	27478	10.2%
1	26970	10.0%
5	23642	8.8%
D	20566	7.6%
A	17679	6.6%
E	9059	3.4%
Other values (2)	5255	1.9%

term
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

36 months	100422
60 months	34382

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	1348040
Distinct characters	10
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	36 months
2nd row	36 months
3rd row	36 months
4th row	36 months
5th row	36 months

Value	Count	Frequency (%)
36 months	100422	74.5%
60 months	34382	25.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
months	134804	50.0%
36	100422	37.2%
60	34382	12.8%

Most occurring characters

Value	Count	Frequency (%)
	269608	20.0%
6	134804	10.0%
m	134804	10.0%
o	134804	10.0%
n	134804	10.0%
t	134804	10.0%
h	134804	10.0%
s	134804	10.0%
3	100422	7.4%
0	34382	2.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	808824	60.0%
Space Separator	269608	20.0%
Decimal Number	269608	20.0%

Most frequent character per category

Value	Count	Frequency (%)
m	134804	16.7%
o	134804	16.7%
n	134804	16.7%
t	134804	16.7%
h	134804	16.7%
s	134804	16.7%

Value	Count	Frequency (%)
6	134804	50.0%
3	100422	37.2%
0	34382	12.8%

Value	Count	Frequency (%)
	269608	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	808824	60.0%
Common	539216	40.0%

Most frequent character per script

Value	Count	Frequency (%)
m	134804	16.7%
o	134804	16.7%
n	134804	16.7%
t	134804	16.7%
h	134804	16.7%
s	134804	16.7%

Value	Count	Frequency (%)
	269608	50.0%
6	134804	25.0%
3	100422	18.6%
0	34382	6.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1348040	100.0%

Most frequent character per block

Value	Count	Frequency (%)
	269608	20.0%
6	134804	10.0%
m	134804	10.0%
o	134804	10.0%
n	134804	10.0%
t	134804	10.0%
h	134804	10.0%
s	134804	10.0%
3	100422	7.4%
0	34382	2.6%

title
Categorical

HIGH CARDINALITY

Distinct	32326
Distinct (%)	24.0%
Missing	5
Missing (%)	< 0.1%
Memory size	1.0 MiB

Debt consolidation	18582
Debt Consolidation	9016
Credit card refinancing	6637
Consolidation	3552
debt consolidation	2929
Other values (32321)	94083

Length

Max length	40
Median length	18
Mean length	16.16875496
Min length	2

Characters and Unicode

Total characters	2179532
Distinct characters	90
Distinct categories	13 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	26973 ?
Unique (%)	20.0%

Sample

1st row	Debt Consolidation and Credit Transfer
2nd row	Debt Consolidation
3rd row	Debt consolidation
4th row	Pay off other Installment loan
5th row	No Regrets

Value	Count	Frequency (%)
Debt consolidation	18582	13.8%
Debt Consolidation	9016	6.7%
Credit card refinancing	6637	4.9%
Consolidation	3552	2.6%
debt consolidation	2929	2.2%
Other	1846	1.4%
Home improvement	1535	1.1%
consolidation	1414	1.0%
Credit Card Consolidation	1360	1.0%
Consolidation Loan	1064	0.8%
Other values (32316)	86864	64.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
consolidation	48423	15.8%
debt	47495	15.5%
credit	24371	8.0%
card	19567	6.4%
loan	16622	5.4%
refinancing	7175	2.3%
home	6069	2.0%
payoff	5687	1.9%
pay	4812	1.6%
off	4128	1.3%
Other values (9044)	121713	39.8%

Most occurring characters

Value	Count	Frequency (%)
o	228622	10.5%
n	191360	8.8%
i	179827	8.3%
	176577	8.1%
e	170126	7.8%
t	161182	7.4%
a	149352	6.9%
d	126176	5.8%
r	93954	4.3%
l	84019	3.9%
Other values (80)	618337	28.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1767172	81.1%
Uppercase Letter	222383	10.2%
Space Separator	176577	8.1%
Decimal Number	6642	0.3%
Other Punctuation	5137	0.2%
Dash Punctuation	1089	< 0.1%
Connector Punctuation	198	< 0.1%
Close Punctuation	110	< 0.1%
Open Punctuation	80	< 0.1%
Math Symbol	72	< 0.1%
Other values (3)	72	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
C	65136	29.3%
D	44617	20.1%
L	15908	7.2%
P	12244	5.5%
R	9625	4.3%
O	9400	4.2%
H	7011	3.2%
I	6884	3.1%
F	6194	2.8%
M	6133	2.8%
Other values (16)	39231	17.6%

Value	Count	Frequency (%)
o	228622	12.9%
n	191360	10.8%
i	179827	10.2%
e	170126	9.6%
t	161182	9.1%
a	149352	8.5%
d	126176	7.1%
r	93954	5.3%
l	84019	4.8%
s	83728	4.7%
Other values (16)	298826	16.9%

Value	Count	Frequency (%)
!	1403	27.3%
/	1257	24.5%
.	985	19.2%
&	486	9.5%
,	471	9.2%
'	219	4.3%
#	103	2.0%
:	73	1.4%
%	57	1.1%
"	56	1.1%
Other values (3)	27	0.5%

Value	Count	Frequency (%)
1	2139	32.2%
2	1559	23.5%
0	1262	19.0%
3	1152	17.3%
4	205	3.1%
5	103	1.6%
6	102	1.5%
9	52	0.8%
8	36	0.5%
7	32	0.5%

Value	Count	Frequency (%)
+	62	86.1%
~	5	6.9%
=	2	2.8%
\|	2	2.8%
>	1	1.4%

Value	Count	Frequency (%)
)	109	99.1%
]	1	0.9%

Value	Count	Frequency (%)
(	77	96.2%
[	3	3.8%

Value	Count	Frequency (%)
	176577	100.0%

Value	Count	Frequency (%)
-	1089	100.0%

Value	Count	Frequency (%)
$	68	100.0%

Value	Count	Frequency (%)
_	198	100.0%

Value	Count	Frequency (%)
`	3	100.0%

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1989555	91.3%
Common	189977	8.7%

Most frequent character per script

Value	Count	Frequency (%)
o	228622	11.5%
n	191360	9.6%
i	179827	9.0%
e	170126	8.6%
t	161182	8.1%
a	149352	7.5%
d	126176	6.3%
r	93954	4.7%
l	84019	4.2%
s	83728	4.2%
Other values (42)	521209	26.2%

Value	Count	Frequency (%)
	176577	92.9%
1	2139	1.1%
2	1559	0.8%
!	1403	0.7%
0	1262	0.7%
/	1257	0.7%
3	1152	0.6%
-	1089	0.6%
.	985	0.5%
&	486	0.3%
Other values (28)	2068	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2179532	100.0%

Most frequent character per block

Value	Count	Frequency (%)
o	228622	10.5%
n	191360	8.8%
i	179827	8.3%
	176577	8.1%
e	170126	7.8%
t	161182	7.4%
a	149352	6.9%
d	126176	5.8%
r	93954	4.3%
l	84019	3.9%
Other values (80)	618337	28.4%

total_acc
Real number (ℝ_≥0)

Distinct	84
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	24.91342245
Minimum	2
Maximum	105
Zeros	0
Zeros (%)	0.0%
Memory size	1.0 MiB

Quantile statistics

Minimum	2
5-th percentile	10
Q1	17
median	23
Q3	31
95-th percentile	46
Maximum	105
Range	103
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	11.10274204
Coefficient of variation (CV)	0.4456530236
Kurtosis	0.5393756326
Mean	24.91342245
Median Absolute Deviation (MAD)	7
Skewness	0.7582357975
Sum	3358429
Variance	123.2708809
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
20	5146	3.8%
22	5111	3.8%
23	5071	3.8%
21	5038	3.7%
19	5025	3.7%
17	5000	3.7%
18	4984	3.7%
24	4932	3.7%
25	4687	3.5%
16	4639	3.4%
Other values (74)	85171	63.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	10	< 0.1%
3	83	0.1%
4	256	0.2%
5	470	0.3%
6	824	0.6%

Value	Count	Frequency (%)
105	1	< 0.1%
98	1	< 0.1%
88	1	< 0.1%
84	1	< 0.1%
83	1	< 0.1%

verification_status
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

Verified	66138
Not Verified	38959
Source Verified	29707

Length

Max length	15
Median length	12
Mean length	10.6986217
Min length	8

Characters and Unicode

Total characters	1442217
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Not Verified
2nd row	Verified
3rd row	Source Verified
4th row	Source Verified
5th row	Not Verified

Value	Count	Frequency (%)
Verified	66138	49.1%
Not Verified	38959	28.9%
Source Verified	29707	22.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
verified	134804	66.3%
not	38959	19.1%
source	29707	14.6%

Most occurring characters

Value	Count	Frequency (%)
e	299315	20.8%
i	269608	18.7%
r	164511	11.4%
V	134804	9.3%
f	134804	9.3%
d	134804	9.3%
o	68666	4.8%
	68666	4.8%
N	38959	2.7%
t	38959	2.7%
Other values (3)	89121	6.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1170081	81.1%
Uppercase Letter	203470	14.1%
Space Separator	68666	4.8%

Most frequent character per category

Value	Count	Frequency (%)
e	299315	25.6%
i	269608	23.0%
r	164511	14.1%
f	134804	11.5%
d	134804	11.5%
o	68666	5.9%
t	38959	3.3%
u	29707	2.5%
c	29707	2.5%

Value	Count	Frequency (%)
V	134804	66.3%
N	38959	19.1%
S	29707	14.6%

Value	Count	Frequency (%)
	68666	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1373551	95.2%
Common	68666	4.8%

Most frequent character per script

Value	Count	Frequency (%)
e	299315	21.8%
i	269608	19.6%
r	164511	12.0%
V	134804	9.8%
f	134804	9.8%
d	134804	9.8%
o	68666	5.0%
N	38959	2.8%
t	38959	2.8%
S	29707	2.2%
Other values (2)	59414	4.3%

Value	Count	Frequency (%)
	68666	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1442217	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	299315	20.8%
i	269608	18.7%
r	164511	11.4%
V	134804	9.3%
f	134804	9.3%
d	134804	9.3%
o	68666	4.8%
	68666	4.8%
N	38959	2.7%
t	38959	2.7%
Other values (3)	89121	6.2%

zip_code
Categorical

HIGH CARDINALITY

Distinct	834
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	1.0 MiB

945xx	1643
750xx	1442
112xx	1431
606xx	1300
100xx	1189
Other values (829)	127799

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	674020
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	20 ?
Unique (%)	< 0.1%

Sample

1st row	782xx
2nd row	481xx
3rd row	809xx
4th row	945xx
5th row	281xx

Value	Count	Frequency (%)
945xx	1643	1.2%
750xx	1442	1.1%
112xx	1431	1.1%
606xx	1300	1.0%
100xx	1189	0.9%
900xx	1180	0.9%
300xx	1163	0.9%
070xx	1125	0.8%
331xx	1120	0.8%
917xx	1050	0.8%
Other values (824)	122161	90.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
945xx	1643	1.2%
750xx	1442	1.1%
112xx	1431	1.1%
606xx	1300	1.0%
100xx	1189	0.9%
900xx	1180	0.9%
300xx	1163	0.9%
070xx	1125	0.8%
331xx	1120	0.8%
917xx	1050	0.8%
Other values (824)	122161	90.6%

Most occurring characters

Value	Count	Frequency (%)
x	269608	40.0%
0	60080	8.9%
1	48251	7.2%
3	43361	6.4%
2	43093	6.4%
9	42463	6.3%
7	39344	5.8%
4	34081	5.1%
5	32479	4.8%
8	32120	4.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	404412	60.0%
Lowercase Letter	269608	40.0%

Most frequent character per category

Value	Count	Frequency (%)
0	60080	14.9%
1	48251	11.9%
3	43361	10.7%
2	43093	10.7%
9	42463	10.5%
7	39344	9.7%
4	34081	8.4%
5	32479	8.0%
8	32120	7.9%
6	29140	7.2%

Value	Count	Frequency (%)
x	269608	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	404412	60.0%
Latin	269608	40.0%

Most frequent character per script

Value	Count	Frequency (%)
0	60080	14.9%
1	48251	11.9%
3	43361	10.7%
2	43093	10.7%
9	42463	10.5%
7	39344	9.7%
4	34081	8.4%
5	32479	8.0%
8	32120	7.9%
6	29140	7.2%

Value	Count	Frequency (%)
x	269608	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	674020	100.0%

Most frequent character per block

Value	Count	Frequency (%)
x	269608	40.0%
0	60080	8.9%
1	48251	7.2%
3	43361	6.4%
2	43093	6.4%
9	42463	6.3%
7	39344	5.8%
4	34081	5.1%
5	32479	4.8%
8	32120	4.8%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	id	member_id	loan_status	addr_state	annual_inc	application_type	desc	dti	earliest_cr_line	emp_length	emp_title	fico_range_high	fico_range_low	grade	home_ownership	initial_list_status	installment	int_rate	issue_d	loan_amnt	mort_acc	open_acc	pub_rec	purpose	revol_bal	revol_util	sub_grade	term	title	total_acc	verification_status	zip_code
0	10148122	NaN	Fully Paid	TX	96500.0	Individual	Borrower added on 12/31/13 > Bought a new house, furniture, water softener, a second car, etc. Got our lives started and now a manageable monthly payment will help keep them going!<br>	12.61	Sep-2003	3 years	Systems Engineer	709.0	705.0	A	MORTGAGE	f	373.94	7.62	Dec-2013	12000.0	1.0	17.0	0.0	debt_consolidation	13248.0	55.7	A3	36 months	Debt Consolidation and Credit Transfer	30.0	Not Verified	782xx
1	10149342	NaN	Fully Paid	MI	55000.0	Individual	Borrower added on 12/31/13 > Combining high interest credit cards to lower interest rate.<br>	22.87	Oct-1986	10+ years	Team Leadern Customer Ops & Systems	734.0	730.0	B	OWN	w	885.46	10.99	Dec-2013	27050.0	4.0	14.0	0.0	debt_consolidation	36638.0	61.2	B2	36 months	Debt Consolidation	27.0	Verified	481xx
2	10119623	NaN	Fully Paid	CO	130000.0	Individual	NaN	13.03	Nov-1997	10+ years	LTC	719.0	715.0	B	MORTGAGE	f	398.52	11.99	Dec-2013	12000.0	3.0	9.0	0.0	debt_consolidation	10805.0	67.0	B3	36 months	Debt consolidation	19.0	Source Verified	809xx
3	10149577	NaN	Fully Paid	CA	325000.0	Individual	NaN	18.55	Nov-1994	5 years	Area Sales Manager	749.0	745.0	A	MORTGAGE	w	872.52	7.62	Dec-2013	28000.0	5.0	15.0	0.0	debt_consolidation	29581.0	54.6	A3	36 months	Pay off other Installment loan	31.0	Source Verified	945xx
4	10129454	NaN	Fully Paid	NC	60000.0	Individual	Borrower added on 12/31/13 > I would like to use this money to payoff existing credit card debt and use the remaining about to purchase a used car that is fuel efficient.<br>	4.62	Dec-2009	4 years	Project Manager	724.0	720.0	B	RENT	f	392.81	10.99	Dec-2013	12000.0	0.0	15.0	0.0	debt_consolidation	7137.0	24.0	B2	36 months	No Regrets	18.0	Not Verified	281xx
5	10149526	NaN	Charged Off	CO	73000.0	Individual	Borrower added on 12/31/13 > I had some water main break and sewer replacement that ran up my Credit cards. I want to consolidate the Credit cards pay off one loan and refurbish my bathrooms.<br><br> Borrower added on 12/31/13 > I had two water main breaks one sewer and one clean water and the cost ran up credit cards expenditures. I want to consolidate the credit cards with a set payment and upgrade my two bathrooms and water heater.<br><br> Borrower added on 12/31/13 > Consolidate credet cards and upgrade bathrooms.<br><br> Borrower added on 12/31/13 > Consolidate credit cards and upgrade two bathrooms.I have been at this job for six years and the job before this one for 24 years. This will make my finances easier to manage. It will provide more efficient bathroom equipment and water heater.<br>	23.13	Jun-1989	6 years	Street Operations Supervisor	669.0	665.0	D	MORTGAGE	f	730.78	19.97	Dec-2013	27600.0	4.0	10.0	0.0	debt_consolidation	27003.0	82.8	D5	60 months	Consolidation of debt and home improve.	24.0	Source Verified	802xx
6	10224583	NaN	Fully Paid	NY	90000.0	Individual	NaN	3.73	Jun-2001	10+ years	Teacher	694.0	690.0	C	MORTGAGE	f	384.68	14.98	Dec-2013	11100.0	1.0	9.0	0.0	other	6619.0	66.2	C3	36 months	Other	12.0	Not Verified	103xx
7	10159584	NaN	Fully Paid	CA	26000.0	Individual	Borrower added on 12/31/13 > While being in college there were expenses that I had to make. At the moment it seemed easy to buy thing on credit, but now that I'm full-time employee paying all credit cards seem impossible and it'll be great to make one consolidated payment to one firm with knowing its for a set amount of months.<br>	25.12	Jan-2007	1 year	Medical Assistant	674.0	670.0	C	RENT	f	333.14	13.98	Dec-2013	9750.0	0.0	12.0	0.0	debt_consolidation	7967.0	52.8	C1	36 months	Debt Consilation	28.0	Not Verified	927xx
8	10139658	NaN	Fully Paid	NM	40000.0	Individual	NaN	16.94	Oct-1998	10+ years	On road manager	664.0	660.0	B	RENT	w	407.40	13.53	Dec-2013	12000.0	0.0	7.0	2.0	debt_consolidation	5572.0	68.8	B5	36 months	Debt consolidation	32.0	Source Verified	871xx
9	10149488	NaN	Fully Paid	TX	39600.0	Individual	Borrower added on 12/31/13 > Just bought a house, and would like a little extra funds to improve aspects of the house such as, duct work, electrical outlets, backyard, and other minor areas.<br>	2.49	Aug-1995	2 years	Surgical Technician	759.0	755.0	B	MORTGAGE	w	157.13	10.99	Dec-2013	4800.0	0.0	3.0	0.0	home_improvement	4136.0	16.1	B2	36 months	For The House	8.0	Source Verified	782xx

Last rows

	id	member_id	loan_status	addr_state	annual_inc	application_type	desc	dti	earliest_cr_line	emp_length	emp_title	fico_range_high	fico_range_low	grade	home_ownership	initial_list_status	installment	int_rate	issue_d	loan_amnt	mort_acc	open_acc	purpose	revol_bal	revol_util	sub_grade	term	title	total_acc	verification_status	zip_code
134794	2367122	NaN	Fully Paid	CA	900000.0	Individual	NaN	10.11	Mar-1980	10+ years	Fremont Bank	709.0	705.0	A	MORTGAGE	f	736.89	6.62	Jan-2013	24000.0	12.0	17.0	debt_consolidation	373687.0	61.5	A2	36 months	Debt Consolidation	51.0	Verified	945xx
134795	2298828	NaN	Charged Off	IL	70000.0	Individual	Borrower added on 12/06/12 > just a little help to get over the hump<br>	10.71	Feb-1995	6 years	JBS United	684.0	680.0	B	MORTGAGE	w	787.10	14.09	Jan-2013	23000.0	4.0	11.0	debt_consolidation	10660.0	53.3	B5	36 months	out of debt	45.0	Verified	618xx
134796	2375433	NaN	Fully Paid	KS	110000.0	Individual	NaN	10.58	Aug-1998	10+ years	First Prebyterian Church	679.0	675.0	B	MORTGAGE	f	843.68	13.11	Jan-2013	25000.0	4.0	10.0	debt_consolidation	4070.0	75.4	B4	36 months	Debt consolidation	19.0	Verified	665xx
134797	2365716	NaN	Fully Paid	CA	203000.0	Individual	Borrower added on 12/05/12 > To transfer higher-rate credit cards to this lower-rate account.<br>	9.74	Sep-1999	5 years	NaN	694.0	690.0	A	RENT	w	666.82	8.90	Jan-2013	21000.0	1.0	10.0	credit_card	14161.0	28.1	A5	36 months	Lending Club Loan	27.0	Source Verified	920xx
134798	2375143	NaN	Fully Paid	TX	35000.0	Individual	Borrower added on 12/05/12 > Debt Consolidation<br>	10.94	Sep-1998	NaN	NaN	724.0	720.0	B	MORTGAGE	w	377.26	11.14	Jan-2013	11500.0	1.0	11.0	debt_consolidation	8158.0	34.8	B2	36 months	My Consolidation	16.0	Verified	783xx
134799	2334898	NaN	Fully Paid	CA	85000.0	Individual	Borrower added on 12/05/12 > pay off credit card debt<br><br> Borrower added on 12/10/12 > pay credit card debt<br><br> Borrower added on 12/12/12 > credit card debt<br>	21.70	Aug-1997	10+ years	local 729	734.0	730.0	B	MORTGAGE	w	341.22	10.16	Jan-2013	16000.0	3.0	10.0	credit_card	8921.0	54.7	B1	60 months	lending club loan	28.0	Verified	910xx
134800	2375068	NaN	Fully Paid	NJ	55500.0	Individual	NaN	23.48	Jun-1991	1 year	Pomptonian food service company	669.0	665.0	D	RENT	f	657.54	18.75	Jan-2013	18000.0	0.0	15.0	debt_consolidation	13102.0	82.1	D3	36 months	consolidation	38.0	Verified	088xx
134801	2374791	NaN	Fully Paid	TX	158000.0	Individual	Borrower added on 12/07/12 > I'm wanting to get this consolidation loan to help my cash flow and make one payment each month. I have a great income and hope to get the note payed off much quicker then the 36 month terms, so I can get back to saving again. Thanks<br>	25.54	May-1990	10+ years	NaN	679.0	675.0	B	RENT	f	565.62	12.12	Jan-2013	17000.0	4.0	7.0	debt_consolidation	5896.0	57.8	B3	36 months	DEBT CONSOLIDATION	19.0	Verified	781xx
134802	2301035	NaN	Fully Paid	CA	200000.0	Individual	NaN	13.81	Aug-2000	9 years	direct telecom inc	709.0	705.0	B	MORTGAGE	f	1048.06	12.12	Jan-2013	31500.0	3.0	13.0	credit_card	31860.0	79.9	B3	36 months	my cc loan	24.0	Verified	915xx
134803	2300581	NaN	Fully Paid	NY	84000.0	Individual	Borrower added on 12/04/12 > Just let debt get a little out of control. Feel it would be much easier to automatically withdraw 1 payment each month from my checking account to pay off my debt instead of paying 4 different locations and having to remember debts due dates.<br>	25.86	Jul-1999	10+ years	Trugreen	734.0	730.0	A	RENT	f	876.13	7.90	Jan-2013	28000.0	0.0	7.0	debt_consolidation	33601.0	68.2	A4	36 months	Consolidation	10.0	Verified	122xx

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters